Senior Software Engineer, Applied AI at TLDR

Matcha; Northern (KY); Hybrid; USD 250,000 - 300,000; Full time

Benefits offered by this job

Home Office Stipend

Learning & Development Stipend

Health benefits

401(k) Plan

Paid Parental Leave

Flexible PTO

Unlimited token budget

Job summary

TLDR is seeking a senior AI product leader to own the development of new agents and platform capabilities across the company. You will design, implement, evaluate, and rollout AI-driven workflows, partnering with the Applied AI PM to prioritize what to build and making small product decisions independently.

You will collaborate with sales, revenue operations, editorial, and people ops to determine where LLMs belong in processes and measure outcomes with well-defined specs and evals.

Qualifications

• 5+ years experience including 2+ years building products and systems with LLMs, with at least one agent you took to production and still own.
• You code fluently with AI tools like Claude Code or Codex.
• You write evals as part of building, not after. You can say how you defined good, what you measured, and what you changed as a result.

Responsibilities

• Own the build out of new agents, skills, and platform capability for teams across TLDR.
• Build and deploy agents end to end, from design through implementation, evals, and rollout to internal users.
• Write the evals and specs that define what good looks like, so workflow quality is measurable rather than anecdotal.
• Partner with our Applied AI PM on what to build, and make the smaller product calls independently.
• Work directly with stakeholders in sales, revenue ops, editorial, and people ops to find where an LLM belongs in their process.

Skills

LLM Experience

Product Management

AI Coding

Tools

Claude Code

Codex

Job description

Who We Are

Product: TLDR’s mission is to increase tech's signal-to-noise ratio.

Today that means the largest network of tech newsletters in the world, with over 8M subscribers covering startups, software engineering, AI, cybersecurity, product, and more. What makes it work is who writes it. Every issue comes from people building in tech, not reporters covering it. Our writers keep their day jobs: two engineers at Coinbase write TLDR Crypto, engineers at DeepMind and Meta write TLDR Dev, researchers at Anthropic and Adobe write TLDR AI, and robotics and datacenter strategy leads at OpenAI and Meta write TLDR Hardware.

If it matters in tech, it's in TLDR. That's what makes TLDR the best place to find what you need to learn.

Team: Our 31-person full-time team includes alumni of TikTok, Reddit, Amazon, Business Insider, Asana, Morning Brew, and Pinterest. We've stayed intentionally small, which means every person here owns a function rather than a slice of one.

Traction: We're bootstrapped, profitable, and on track for $35M in revenue this year - after $9M in 2024 and $20M in 2025. The advertisers who fund it want tech's decision-makers: AWS, Google Cloud, Anthropic, Slack, Notion, and GitHub.

About the Role

TLDR's Applied AI program runs on one thesis: every process at the company should get better automatically as model capabilities improve. An LLM sits in the loop on every workflow, and the work of the people around it shifts from clicking and typing toward writing specs and evals and deciding what good looks like.

In this role, you will:

• Own the build out of new agents, skills, and platform capability for teams across TLDR.

• Build and deploy agents end to end, from design through implementation, evals, and rollout to internal users.

• Write the evals and specs that define what good looks like, so workflow quality is measurable rather than anecdotal.

• Partner with our Applied AI PM on what to build, and make the smaller product calls independently.

• Work directly with stakeholders in sales, revenue ops, editorial, and people ops to find where an LLM belongs in their process.

What Success Looks Like

• Every workflow at the company improves as model capabilities improve.

• Teams write specs and evals and define what good looks like, rather than executing manually, and their processes improve as models improve without anyone rebuilding them.

• Work becomes increasingly push vs pull, by default work is done by LLMs and humans are brought in as needed.

About You

• 5+ years experience including 2+ years building products and systems with LLMs, with at least one agent you took to production and still own.

• You code fluently with AI tools like Claude Code or Codex.

• You write evals as part of building, not after. You can say how you defined good, what you measured, and what you changed as a result.

You’ll Thrive Here If…

• You ship end to end and don't wait for someone to spec the small stuff.

• You have product judgment: you can say what you chose not to build, and why.

• You're comfortable in a domain where settled practice doesn't exist yet.

• You can sit with non-engineering stakeholders and find where an LLM belongs in their process.

• The way you build has changed as models have gotten better, and you treat capability improvement as a design input.

• You want surface area across nearly every function of a profitable, bootstrapped company, with no legacy systems to fight, direct CEO access, and an unlimited token budget.

Why You'll Love It

Compensation:

• Base compensation: $250,000 - $300,000

• Annual company performance bonus: $25,000 - $60,000

Location: We're 100% remote across the US and Canada. Work where you want - our bands are set to tier-1 city rates wherever you live.

Team Events: Biannual team offsites. Most recently we’ve gone to New Orleans, San Diego and Park City!

Time to Recharge: Flexible PTO. Most of the team takes 2–3 weeks a year, plus holidays.

Health Benefits: Comprehensive medical, dental and vision benefits with a 100% paid option

401(k) Plan: Empower 401(k)

Paid Parental Leave

Home Office Stipend: Whatever makes you productive - standing desk, second monitor, chair, walking pad.

Learning & Development Stipend: For anything that makes you better at your work, and for AI tools especially. Don't ration your tokens.

Press and Publications

• Inc story on how TLDR was founded

• Pricing and demographic information in TLDR’s latest media kit